We publicly release the anonymized song_embeddings.parquet user_embeddings.parquet user_features_test.parquet user_features_train.parquet user_features_validation.parquet datasets, with each of the TT-SVD or UT-ALS versions of embeddings, from the music streaming platform Deezer, as described in the article "A Semi-Personalized System for User Cold Start Recommendation on Music Streaming Apps" published in the proceedings of the 27TH ACM SIGKDD conference on knowledge discovery and data mining (KDD 2021). The paper is available here. These datasets are used in the GitHub repository deezer/semi_perso_user_cold_start to reproduce experiments from the article. Please cite our paper if you use our code or data in your work.